Applying the Francis-Hunston Model to a one-to-one EFL conversation

Size: px
Start display at page:

Download "Applying the Francis-Hunston Model to a one-to-one EFL conversation"

Transcription

1 Unverty of Brmngam Centre for Engl Language Stude September 2006 Module 4 Claroom & Spoken Dcoure Applyng te Franc-Hunton Model to a one-to-one EFL converaton by Mcael wane-salovaara Queton SD/05/03 ecord part of a converaton n Engl tat take place n one of te followng tuaton (or mlar), a outlned by Franc and Hunton (Franc, G. and Hunton, S., 'Analyng everyday converaton' n Coultard, 1992: ): caual converaton between frend and famly member cld-adult talk commercal tranacton profeonal ntervew rado pone-n Trancrbe part of your recordng, coong a part n wc tere are farly frequent alternaton of peaker. Make an analy of te trancrbed data, ung te categore propoed by Franc and Hunton (bd. p. 125 and ff.). Preent your analy a Part of your agnment. Comment on ow eay t wa to ft your data to te categore and te uefulne of t knd of analy for undertandng te knd of communcaton you ave analyed. Preent your commentary a Part of your agnment.

2 Module 4 Claroom & Spoken Dcoure Applyng te Franc-Hunton Model to a one-to-one EFL converaton 1.0 ntroducton Te claroom dcoure model et up by Snclar and Coultard place te teacer a te focu, te drector, te ntator of wat goe on n te claroom. To t end te ntaton-repone-feedback (F) excange model (1992:3) tey et up work well wtn t controlled pedagogc ecoytem. One of te dtngung feature of te Snclar-Coultard claroom dcoure model te domnant role te teacer play. However, n te dcoure extract examned for t paper, an EFL converaton leon, te learner take greater ntatve tan wat may be te cae n a typcal claroom a defned by Snclar and Coultard. Conequently, te EFL converaton leon wa examned ung te Franc-Hunton model wc proved to be an effectve tool to dentfy and accommodate a wder array of dcoure component. Alo anoter gnfcant factor n coong te Franc-Hunton model wa te learner tated objectve of developng converatonal kll T paper wll apply te Franc-Hunton model (ee Appendce.1 and.2) to an EFL converaton leon. n te proce of analyng and commentng on te trancrbed data wll alo demontrate tat te category of everyday converaton can be expanded to nclude ome language teacng/learnng tuaton. However, frt want to dcu te callenge n coong te mot approprate model. 1.1 Problem of clafcaton (ee Appendx V) Of te many callenge n preparng t paper wa to determne wc dcoure model to ue. f followed te nomenclature would ave automatcally ued te Snclar-Coultard model becaue te extract wa taken from a teacng/learnng context. However, furter nvetgaton nto te claroom dcoure model began to reveal ome 1

3 gnfcant contradcton. Te mot obvou wa tat te leon led wa n a café over coffee and not a claroom over a lectern. Next wa tat dd not actually lead a muc a facltate te leon; te learner le a tudent and more lke a clent. Were te claroom leon decrbed by Snclar and Coultard (1992:1) reembled a Type A teacer controlled yllabu, te drecton of leon content wa a learner nfluenced Type B yllabu (ee Wte 1988; Yalden 1983). Wen turned to te Franc-Hunton model agan ad to look beyond te nomenclature and ee tat Franc and Hunton were not o muc fxed on everyday converaton a tey were on te flud qualty typcally found n everyday tuaton. Converely, Snclar and Coultard were lookng at a more rgd and predctable dcoure n order to develop ter model. Once could get beyond wat everyday converaton mpled and looked at te contrat wt claroom dcoure t became clear tat te Franc-Hunton model wa te a more effectve tool n revealng te detal of an EFL converaton for everal reaon. Frt, te teacer n t dcoure play a le autortaran role a te knower (Wll, D. 1992). Altoug te teacer tll play a domnate role n leadng te converaton tere more opportunty for te negotaton of role. Toug not n te trancrpt, te learner a ometme uggeted a cange of topc or abruptly canged topc wtout warnng. Second, toug pontanety dered t mportance can be overtated. Conder, for example, converaton at a op, n a doctor offce, or between a cld and parent. Tey uually follow famlar dcoure pattern tat enable a moot excange of nformaton. Even toug te converaton between T and S may be le pontaneou, t not o dfferent from many type of everyday dcoure. Fnally, n term of nner and Outer language te EFL converaton motly Outer rater tan te combnaton of te two common n many claroom (Wll, J. 1992: 162ff). 1.3 Lterature revew Hallday (1961) talked about categorng te teory of grammar wtn a dcoure rank-cale erarcy from te larget, Leon, to te mallet, Act. Later, Scegloff and Sack decrbed adjacency par to expaln ow an utterance can lead to a retrcted lt 2

4 of expected repone uc a greetng-greetng and apology-acceptance (McCarty 1991:120; ee Scegloff, E.A. and Sack, H: 1973 n Jawork and Coupland 1999). Buldng upon te dea tat poken dcoure a an dentfable tructure tat can be analyed Snclar and Coultard (1975) examned te controlled dcoure of te claroom and dentfed F (ntaton, epone, and Follow-up) a te element of tructure realzed by te accompanyng move openng, anwerng, and follow-up. T approac wa later modfed by Coultard and Montgomery (1981) and te move were relabelled a elctng,, and acknowledgng wt te recognton tat bot ntaton and epone can be realzed by an move and epone, and Follow-up can be realzed by an acknowledgng move. (ee Fgure 1). (ntaton) elctng (epone) F (Follow-up) acknowledgng Fgure 1. Te reved relatonp between F and Move clae To account for an utterance tat bot predcted and predctng te element of tructure / (epone/ntaton) wa added (1995: 149). T produced a defnton of an excange: (/) (F n ) Accordng to t defnton only and are neceary to complete and excange. / optonal to allow for two move wtn one excange. F alo optonal and can occur more tan one tme. 3

5 Te cart n Appendce.1 and.2 ow te relatonp between te fve rank (Act, Move, Excange, Tranacton, and nteracton) from mallet to larget baed on te Franc-Hunton model (refer to te cart for greater detal). Tere are 32 Act type lotted nto te poton of pre-ead, ead, and/or pot-ead (ome Act type are lotted nto more tan one poton). Tee 32 Act type realze 8 clae of Move wc are tructured nto F a dcued above. Te 8 clae of Move realze 2 Excange type of wc organatonal furter dvded nto 4 ub-clae realzng Prelmnary and Termnal Tranacton tructure and converatonal nto 6 ub-clae realzng te Medal Tranacton. A Tranacton alo referred to a te converaton topc. Te fnal rank nteracton not a prece a te oter four rank, but can be undertood a te peakng tuaton. 4

6 2.0 Part : Analy 2.1 Data Source Te data ource ued for analy wa a one-to-one EFL converaton leon ad done wt a Japanee bune man (referred to a S ) on 24 Aprl, 2006 n a Oaka cafe. Te leon wa recorded wt a Sony dgtal voce recorder. Te leon telf wa 120 mnute from wc extracted a egment of jut under 8 mnute for analy. Wtn te 120 mnute leon tere were 3 dtnct topc area (Tranacton): Oaka tran; recordng and copyng audo fle; Japanee clacal muc conductor. Te extract taken from te Oaka tran Tranacton typcal of te relatvely g number of excange trougout te wole leon. Te trancrpt contan 865 word wt 471 word poken by T and 394 by S 2.2 ank nteracton Ung te rank cale ued by Franc and Hunton (1992: ) te nteracton a one-to-one EFL converaton leon between myelf, coded a T n te analy, and an Oakan buneman, coded a S. Te excerpt taken from md converaton of te frt of tree topc unt (1992: 140). t wa elected a an example of te relatvely g number of excange tat typcal of t recordng. n regard to te complete recordng te boundary tranacton realzed a P (Prelmnary) and T (Termnal) were not recorded for te practcal reaon tat bot T and S frt meet n te otel lobby and ten proceed to te café for te leon at wc tme te recorder turned on. Te walk from te lobby to te café accompaned by a greetng and pontaneou converaton wc are often mlar to te prelmnare found n a doctor offce (1992:140 referrng to Coultard 1981:14) n tat tey often ave no connecton to te leon converaton telf. Smlarly te lead up to leave-takng 5

7 not recorded a t deal wt leon payment and cedulng wc are not part of te leon proper. However tey do functon a openng and clong tranacton (1992:141) but to record te openng tranacton would be ocally awkward walkng troug a publc pace wt a recordng devce n and. A for te clong tranacton proprety ugget tat te recordng end pror to dcung bune detal Tranacton Te tranacton begn at 9:41 after recordng begn, rougly 12~13 mnute after te ntal greetng. Te topc unt actually a ub-topc unt a t part of a longer dcuon about tran ervce n Oaka. Te analy begn at a paue and fne mdtopc approxmately egt mnute later. Te fn arbtrary, coen for reaon of pace and te uffcent quantty and qualty of te data ample Excange Te number of excange totalled 44 wt T ntatng 34 and S 10 excange. T breakdown mlar to te telepone converaton analyed by Franc and Hunton wt 37 excange n total - Speaker A: 26 excange; Speaker B: 11 excange excludng te openng and clong tranacton (1992: ; alo ee Appendx ). T eem to ndcate tat te dcoure ntator ( T and Speaker A) tended to be te more domnate peaker n term of te number of excange. A for te excange temelve nform wa te mot frequent wt a total of 12 excange (T:8, S:4). Of tee 12 tere were 6 ncomplete nform excange (ee Excange 2, 4, 10, 17, 19, 24) evenly dvded between T and S. T ndcated tat S wa more reponve tat wat mgt be found te claroom decrbed by Snclar and Coultard (1992: 1). Te telepone converaton (1992: ) ow mlar reult wt 10 excange (A:6; B:4). Next wa Clarfy wt 11 excange (T:8; S:3) of wc all but one are realzed by te elctng move. Agan t comparable to te telepone converaton wt 7 excange (A:6; B:1) 6

8 Te lnkng of te one-to-one EFL converaton to te everyday-type telepone converaton meant to ow tat an argument can be made to apply te Franc and Hunton model to a teacng/learnng tuaton. T argument may be weakened by te reult of te oter excange: e-ntaton wt 9 excange (T:6; S:3); Elct wt 7 excange (T:7; S:0); and epeat wt 2 excange (T:2; S:0). Alternatvely te dfference converaton genre may account for te dfference. T queton beyond te purpoe of t paper and wll not be purued any furter. Grouped togeter tee 18 excange (T: 15; S:3) along wt te 11 Clarfy excange ow te domnance of te teacer (T: 23; S: 6). Te comparatve departure perap reflect te caractertc of te dfferent genre and te pecfc converaton temelve Move Te number of move totalled 109 (ee Appendx.1). An examnaton of te dtrbute of act realzng, elctng, and acknowledgng reveal a pattern of domnance accordng to peaker. T own to be te domnant peaker more often becaue realzed by 12 obervaton wc more aggreve tan nformatve becaue t ued to et up an excange by ndcatng to te ltener were te converaton movng (for example lne 96). Te more pave nformatve on te oter and uually te econd of an adjacency par (Sack. n t cae S n te move (15) tended to be led by te more aggreve T (for example lne 55/57, 96/98,150/151). Smlarly te elctng move ow tat T took te ntatve te majorty (71%) of te tme. Agan te ame pattern found wt te acknowledgng move. Altoug tere party, T emerge a te domnant peaker becaue of te ger number of 7

9 termnate act (9). Meanwle S recorded a ger number of receve act (8). Gven tat te dcoure part of a leon between a teacer and an EFL learner te domnance of T not unexpected. t ould be noted tat S wa not entrely pave and dd move te converaton everal tme Act At te rank of act te pattern of T beng te more domnate peaker. Of te 137 act te mot numerou wa nformatve wt 23 occurrence (T:10; S:13). t wa plt between nform (12) and Elct (11) excange (ee Appendce.2 and V). Here te majorty of te occurrence are wt S a nformatve realzng nform tend to play te econd peaker role. At nformatve realzng Elct we can agan ee te relatve pavty of S. Contnung on wt obervaton wt 14 occurrence (T12; S:2) Te domnate peakng role T Summary of Analy Ung te Franc-Hunton model wa effectve n dentfyng T a te domnant peaker toug not excluvely. Gven te context of an EFL leon tat reult wa to be expected. Wat partcularly ueful te applcaton of t data n gudng te learner to be a more complete converatonalt by takng te ntatve. 3.0 Part Comment 3.1 ntroducton to Comment Below are a amplng of te many nteretng pattern, caractertc and dffculte. uc a turn-takng and nterrupton. Partcularly dffcult wa te codng of wat call peaker momentum coupled wt utterance by te econd peaker tat ad eemngly no effect on wat te frt peaker wa ayng. 8

10 3.2 Turn-takng Sack ponted out tat n contrat to pre-allocaton ytem uc a a debate or peec a elf-electng turn-by-turn allocaton ytem tend to produce peakng turn tat are a entence long (Coultard 1985: 64). Settng ade te queton of wat conttute a entence n poken dcoure, epecally converaton, te one-to-one converaton examned for t paper a example of t turn-takng ytem. Of te many turn taken wll glgt two example Turn-takng: elevance Te tranton for excange 12 to excange 13 wa dffcult to code becaue altoug S took turn on cue wat e ad wa not wat Coultard call a relevant next utterance (1985: 62). Wat S ad n lne 47 took me by urpre at te tme e ad t becaue wa expectng a repone drectly connected to wat ad jut ad about my tran lne. However S ad te ntatve and decded a dfferent relevance pckng up on a pont about tran lne. n everyday converaton te queton of relevance not alway clear cut between peaker. n lgt of t ambguty decded to ndcate t ambguty by markng te border between excange 12 and 13 wt a old lne and code excange 13 a bounded re-ntaton elct excange wc reconnect wt wat wa ad early about tran taton. T type of turn-takng not uncommon n a learnng context were te learner buy tnkng about wat to ay and not focued on wat beng ad and tu make a repone out of ync. Smlarly n everyday converaton wen te econd peaker focued on makng a partcular pont /e wll often gnore wat wa jut ad and jump to wat /e want to ay. 42 T: o we don t ave te problem tat you ave were two local tran. ob b e-ntaton S: yea, yea rec 44 T: So m 9

11 45 T: you m local tran and you tnk, a, te next one gong to go ref 46 T: No, you don t ave tat problem on Mdouj. ter pot- (ncomplete) 47 S: Wen arrve pre- b e-ntaton S: wen arrved at platform ob 49 T: mm 50 S: already mne wa comng Turn-takng: Two Ue of orry Te econd example a to do wt te ue of orry. n te frt ntance orry wa ued a a marker to ndcate elf correcton. n lne 34 Excange 9 orry wa ued to amend wat wa jut ad jutfyng te repeat excange. Te econd ntance of orry n lne 41 Excange 11 t wa ued by T to aert frt tarter... rgt to contnue (1985:62). 32 T: &and ometme Abko umm but a uually t alternatng Nakamozu, Tennoj, Nakamozu, Tennoj. Durng te peak perod umm f tey ave an rregular pattern, t alway Tennoj two tran Tennoj. 33 S: a (ncomplete) 34 T: a orry, [11:00] b epeat 9 35 T: Nakamozu. Two tran to Nakamozu. Never two tran n a row& ob 36 S: &mm& 37 T: &to Tennoj& 38 S: &mm& 39 T: &So f& pre- nform (ncomplete) S: &[unclear]& [tre to nterrupt] (ob) () () (ncomplete) T: &Sorry, ter 42 T: o we don t ave te problem tat you ave were two local tran. ob b e-ntaton S: yea, yea rec 10

12 n contrat to lne 34 Excange 9 te ue of orry n lne 100 Excange 26, alo a marker to ndcate elf correcton, wa ued to amend wat te peaker wa about to ay. 100 S: and a (#) wen a (#) nform (ncomplete) 101 S: a orry a m b e-ntaton S wen wen arrved at Morguc taton Late pot- comment At lne 65 aumed S wa fned peakng nce e jut anwered my queton o tarted a new excange. Jut a wa about to make my pont n lne 66 S nterrupted wt a comment (lne 67) tat wa obvouly connected to lat tatement and not to wat wa n te proce of ayng. Ung te telepone converaton coded by Franc and Hunton a an example (ee lne 59-62: 158) encloed lne 67. However, becaue te comment wa added after te man pont wa made felt tat t dd not mert t own excange. ntead labelled t a excange 16b and coded t a f excange 17 dd not ext. 63 T: And te em-expre? ret elctng b Clarfy 16a 64 S: em-expre and a (#) Green and wte. 65 T: Okay, [fallng ntonaton] pre- nform T: caue a & (ncomplete) 67 S: &t very mall. [laug] com pot- nform 16b 3.4 Te n-joke A often te cae wt two peaker wo know eac oter well n-joke become part of te dcoure. n t cae te n-joke refer to a prevou leon. n lne 87 S appeared to fn but wt te quck ncluon of te n-joke e began a new excange coded a re-ntaton wc added to prevou tatement. Te dotted lne ndcate 11

13 t cloe lnkage between te two excange. 86 T: Don t tey make an announcement? n.pr elctng Elct S: Sometme, ometme e ad& rec 88 S: ometme [bot laug] [an njoke] com pot- 89 T: &ometme 90 S: not every tme& b e-ntaton Momentum Te tructure contradct te gudelne for codng dcoure. A wa te cae wt excange 21, t excange a an utterance wc no effect on te momentum of te utterance by S. Altoug te move n lne 129 could ave been coded a (ncomplete) and lne 131 a at b, decded to code all te move wtn te ame excange to mantan te momentum of peaker S. 126 S: o (#) [fallng ntonaton] m nform S: and (#) now (#) pre- 128 S: actually now (#) tmetable very good ob 129 S: but but& qu pot- 130 T: &For now& (ter) () () () 131 S: & ave to ave to be careful. [laug] qu pot- 3.6 ncomplete Utterance Excange 36 preented a problem dfferent tan toe found n excange 21 and 31. Lke excange 21 and 31 peaker S nterrupted T, owever, n t ntance te ntonaton uggeted tat e wa gong to tart a new excange rater tan comment on wat wa ad. To reflect tat ntenton agned t a an ncomplete excange, but not 12

14 encloed. Snce te momentum of peaker T dd not cange and no nformaton wa ared marked excange 37 between dotted lne. A wt excange 31, te codng of excange 38 carre on unnterrupted from excange 36. Smlarly codng t a an nq elctng move at jutfed becaue tere wa no retart or a return. Speaker T contnued a f peaker S ad never made an utterance. T goe agant te gudelne, owever, te lnear nature of te analy doe not alway ealy allow for conformty. n tee cae t eemed tat followng te momentum of te peaker offered a workable oluton. 146 T: a But, [16:00] m elctng Elct T: mean a everal year ago tey canged te cedule pre- 148 S: yea 149 T: only local& (ncomplete) 150 S: &ayy...& (ncomplete) T: wen dd tey cange (#) ow long, two year, tree year? nq elctng Elct S: Two a two two year. Tabun maybe many people wa angry and u Kean [laug] 152 S: Kean needed needed to cange. [laug] com 153 T: yea (#) ter F 4.0 Concluon Some of te dffculte n codng, and ndeed coong te approprate model, can be attrbuted to te uncertanty to wc genre te EFL converaton leon dcoure belong. However, te reult ave own tat te Franc-Hunton model can be appled to ome teacng tuaton, pecfcally leon were te learner a a greater role and opportunty to ntate te converaton and excange lke toe found n a Type B yllabu. Toug Franc and Hunton dd not ntend te model to be ued n an ESL/ EFL context t doe ave applcaton n examnng peaker domnance, fluency, turntakng, nterrupton, clarfcaton, and of nteret to me, ow te reult reflect te learner cultural peakng pattern (.e. takng a le domnant peakng role wen 13

15 peakng wt a teacer). Altoug t not urprng to fnd tat T n te role of teacer played a domnate role, toug not excluvely o, n te converaton, te tated objectve of te learner ugget tat e need to take more ntatve n order to feel comfortable peakng from bot poton. Alo ome ntance of turn-takng ave revealed tat te common EFL learner problem of mng wat wa jut ad and repondng to wat wa ad a few turn prevou. Fnally, from dong te trancrbng and codng can begn to ee n data form wat meant by fluency. On t lat pont want to nvetgate furter n my dertaton. 14

16 eference Coultard, M. (1985) An ntroducton to Dcoure Analy. (2 nd edn.). Harlow: Longman. Coultard, M. (ed.) (1992) Advance n Spoken Dcoure Analy. London: outledge. Coultard, M., Montgomery, M. and Brazl, D. (1981) Developng a Decrpton of Spoken Dcoure. n Coultard, M. and Montgomery, M. (ed.) (1981) Stude n Dcoure Analy. London, Boton, Melbourne and Henley: outledge and Kegan Paul. Franc, G. and Hunton, S. (1992) Analyng everyday converaton. n Coultard, M. (ed.) (1992) Advance n Spoken Dcoure Analy. London: outledge. Hallday, M.A.K. (1961) Categore of te teory of grammar Word 17, McCarty, M. (1991) Dcoure Analy for Language Teacer. Cambrdge: Cambrdge Unverty Pre. Scegloff, E.A., Sack, H. (1973) Openng Up Clong. n Jawork, A. and Coupland, N. (ed.) (1999) Te Dcoure eader. London: outledge. Wte, onald V Te ELT Currculum: Degn, nnovaton and Management. Oxford: Blackwell. Wll, D. (1992) Caugt n te act: ung te rank cale to addre problem of delcacy. n Coultard, M. (ed.) (1992) Advance n Spoken Dcoure Analy. London: outledge. Wll, J.. (1992) nner and Outer: Spoken dcoure n te language claroom. n Coultard, M. (ed.) (1992) Advance n Spoken Dcoure Analy. London: outledge. Yalden, J. (1983) Te Communcatve Syllabu: Evoluton, Degn & mplementaton. Oxford: Pergamon. 15

17 Appendx.1 Franc-Hunton everyday converaton model (organzatonal) cla V Act e.. cla V Move e.. Excange Tranacton nteracton marker (m) framer (fr) gnal () ead () (1) Framng Frame (Fr) 1a Organzatonal boundary marker (m) framer (fr) tarter () gnal () pre-ead (pre-) Prelmnary (P) metatatement, (m) concluon (con) greetng (gr) ummon (um) comment (com) marker (m) tarter () ead () pot-ead (pot-) gnal () pre-ead (pre-) (2) Openng ntaton () 1b Organzatonal () tructurng () greet () ummon nteracton acquece (acq) reply-greetng (re-gr) reply-ummon (re-um) reject (rej) ead () (3) Anwerng epone () Termnal (T) comment (com) pot-ead (pot-) Adapted from Franc. G & Hunton, S (1992) Analyng everyday converaton, n Coultard, M, 1992, Advance n Spoken Dcoure Analy. outledge: London. 16

18 Appendx.2 cla marker (m) tarter () (, v) nqure (nq) (, v) neutral propoal (n.pr) (, v) marked propoal (m.pr) comment (com) prompt (p) marker (m) tarter () V Act () nformatve () () obervaton (ob) b (v) return (ret) b (v) loop (l) b (v) prompt (p) Franc-Hunton everyday converaton model e.. gnal () pre-ead (pre-) ead () pot-ead (pot-) gnal () pre-ead (pre-) ead () V Move cla (4) Elctng (5) nformng e. ntaton () Excange Tranacton nteracton qualfy (qu) comment (com) marker (m) tarter () drectve (d) comment (com) prompt (p) marker (m) tarter () (, v) nqure (nq) (, v) neutral propoal (n.pr) (, v) marked propoal (m.pr) () nformatve () () concur (conc) () nformatve () () concur (conc) termnate (ter) react (rea) endore (end) termnate (ter) react (rea) endore (end) comment (com) prompt (p) marker (m) tarter () receve (rec) () concur (conc) qualfy (qu) comment (com) marker (m) tarter () receve (rec) b (v) return (ret) b (v) loop (l) b (v) prompt (p) () qualfy (qu) () confrm (conf) () reject (rej) () qualfy (qu) () confrm (conf) () reject (rej) () concur (conc) qualfy (qu) comment (com) marker (m) receve (rec) receve (rec) reformulate (ref) protet (prot) comment (com) termnate (ter) marker (m) tarter () receve (rec) () reject (rej) beave (be) comment (com) qualfy (qu) marker (m) receve (rec) receve (rec) reformulate (ref) protet (prot) comment (com) termnate (ter) pot-ead (pot-) gnal () pre-ead (pre-) ead () pot-ead (pot-) gnal () pre-ead (pre-) ead () pot-ead (pot-) gnal () pre-ead (pre-) ead () pot-ead (pot-) gnal () pre-ead (pre-) ead () pot-ead (pot-) gnal () pre-ead (pre-) ead () pot-ead (pot-) gnal () pre-ead (pre-) ead () pot-ead (pot-) gnal () pre-ead (pre-) ead () pot-ead (pot-) (7) Drectng (4) Elctng (5) nformng (5) nformng (6) Acknowledgng (8) Beavng (6) Acknowledgng epone/ ntaton (/) epone () Follow-up (F) 2 Converatonal () elct () nform Adapted by Mcael wane-salovaara (2006) from Franc. G & Hunton, S (1992) Analyng everyday converaton, n Coultard, M, (1992), Advance n Spoken Dcoure Analy. outledge: London. () drect (v) clarfy-bound elct (v) repeat-bound elct (v) re-ntaton-bound elct Medal (M) nteracton 17

19 Appendx : Excange: A comparon of excange between a one-to-one EFL converaton leon and a telepone converaton. Excange EFL converaton telepone converaton Total (T, S) Total (A, B) Total number of excange 46 (33. 12) 37 (26, 11) Converatona l () elct 7 (7, 0) 10 (7, 3) () nform 16 (10, 6) 10 (6, 4) () drect (bound elct) (v) clarfy 11 (8, 3) 7 (6, 1) (v) repeat 2 (2, 0) 4 (2, 2) (v) rentaton 9 (6, 3) 2 (1, 1) Source: (1) EFL converaton - ee Appendx V; (2) telepone converaton - ee p Franc, G. and Hunton, S. (1992) Analyng everyday converaton. n Coultard, M. (ed.) (1992) Advance n Spoken Dcoure Analy. Appendx.1 Move Occurrence Move Lne occurrence Total (T, S) 21 (16, 5) elctng 19 (16, 3) / 2 (0, 2) 42 (23, 19) 26 (16, 10) / 4 (4, 0) 12 (3, 9) 33 (13, 20) acknowledgng 20 (6, 14) F 13 (7, 6) drectng beavng 1 (0, 1) 18

20 Appendx.2 Act Occurrence accordng to Move Move Move Total (T, S) 42 (23, 19) elctng 21 (16, 5) Act T Act S m 5 m rec -- rec ob 12 ob 2 rej 1 rej -- com 1 com 6 qu qu 1 m 3 m ret 7 ret 3 nq 5 nq 1 n.pr 2 n.pr 1 p 1 p -- m 2 m -- rec 2 rec 9 ref 3 ref 2 acknowledgng 33 (13, 20) prot 1 prot -- rea 1 rea 4 ter 8 ter 4 com -- com 2 beavng 1 (0, 1) be -- be 1 19

21 1. Act (total 152) Label abbr. Occurrence T lne # S lne # framer fr marker m 13 (10, 3) tarter elctng (4, 1) (11, 3) metatatement m concluon con acquece aqu greetng gr reply-greetng re-gr ummon um reply-ummon re-um nqure nq 6 (5, 1) neutral propoal n.pr 3 (1, 2) marked propoal m.pr return ret 10 (7, 3) loop l prompt p 1 (1, 0) 82 obervaton ob 14 (12, 2) (2, 6) nform / (1, 0) 144 nformatve (1, 2) (0, 1) Elct / (2, 0) (4, 4) concur conc confrm conf qualfy qu 1 (0, 1) 131 reject rej 1 (1, 0) 19 termnate ter 12 (8, 4) receve rec acknow. (0, 9) F (2, 0) react rea 5 (1, 4) reformulate ref 5 (3, 2) endore end protet prot 1 (1, 0) 141 drectve d beave be 2 (0, 2) comment com 10 (1, 8) engage 18 (8, 10)

22 Appendx Act Label Label framer abbr. fr ealzed by... a cloed cla of tem: () OK, (all) rgt, anyway and ter varant, were te tem precede an excange-ntal move ead ( anyway may alo be embedded n a move ead); () well, now, good and ter varant, were te tem precede an excange-ntal move ead and ad wt g key fallng ntonaton followed by lent tre. marker m te ame cloed cla of tem a fr: () OK etc. were te tem precede a non-excange-ntal move ead; () well etc. (alo o, er(m), and look ) were not ad wt g key fallng ntonaton. tarter tatement, queton, command or moodle tem. metatatement m tatement, queton or command. concluon con a tatement or queton often wt anaporc reference. acquece acq ye and oter tem ndcatng aent, bot verbal and non-verbal. May be realzed by lence, nterpreted a a default mecanm wereby falure to protet (rej) an ndctaon of acquecence. greetng reply-greetng ummon replyummon gr re-gr um re-um a cloed cla of tem wc form te frt-par part of te adjacency par ued n te rtual of greetng and leave-takng: ello,, good mornng, (good)bye(-bye), ave a nce/good day, be eeng you and ter varant. a cloed cla of tem wc form te econd-par part of te adjacency par ued n te rtual of greetng and leave-takng: ello,, good mornng, (good)bye(-bye), fne tank )and you), tank you, ame to you, yea ee you, and ter varant. te rngng of te telepone, a knock at te door, etc., or te callng of omebody name. te tem ued to anwer a telepone ( ello, te gvng of one number, etc.) or te door (openng t, callng come n, etc.) or by ye, wat? and oter ndcaton of attenton (bot verbal and non-verbal) gven upon earng one name called. nqure nq queton wc eek nformaton a oppoed to a ye or no anwer,.e. w-queton and ellpted form of tee. neutral propoal n.pr queton wc eek a ye or no anwer,.e. queton begnnng Do you, Are you, etc. and ellpted form tee. ealzaton and Functon ealze... Wen t precede an m or con t realze te pre-ead of an openng move n a Structurng excange; wen t precede any oter excange-nttal move ead t realze te ead of a framng move n a Boundary excange. te gnal element of all move. te pre-ead of an openng, anwerng, elctng,, drectng or beavng move. te ead of an openng move n a Structurng excange. te ead of an openng move n a Structurng excange. te ead of an anwerng move n a Structurng excange. te ead of an openng move n a Greet excange. te ead of an anwerng move n a Greet excange. te ead of an openng move n a Summon excange. te ead of an anwerng move n a Summon excange. te ead of an elctng move except at b n Clarfy and epeat excange. te ead of an elctng move. except at b n Clarfy and epeat excange. Functon to mark boundare n te converaton, were uc an nterpretaton content wt conderaton of topc. to mark te onet of a move to provde nformaton about or drect attenton toward te act realzng te move ead. to tructure te converaton propectvely n ome way, and to obtan a warrant for dong o. to te up a partcular topc, and to obtan a warrant for dong o. to provde a warrant for a uggeton a to propectve (m) or retropectve (con) tructurng made by te oter partcpant n a two-party converaton. elf-explanatory. elf-explanatory. to engage anoter partcpant n a converaton or to attract /er attenton. to ndcate wllngne to partcpate n a converaton, or tat one gvng one attenton. to elct nformaton. to elct a decon between ye and no. Example

23 l Appendx Act Label (cont.) Label marked propoal abbr. m.pr ealzed by... queton wc eek a ye or no anwer, were te form of te queton ndcate te polarty of te expected anwer,.e. queton begnnng Don t you, Aren t you, etc. t alo realzed by declaratve ad wt quetonng ntonaton and declaratve followed by tag queton. return ret queton, often ellpted. loop a cloed cla of tem: pardon, wat, e, agan, and ter varant, ad wt rng ntonaton. prompt p a cloed cla of tem: a (wt rng ntonaton), come on, go on gve me and anwer, gue and ter varant. obervaton ob tatement. nformatve tatement or by ye and no tem and ter varant, bot verbal (e.g. (don t) tnk o ) and non-verbal (e.g. nod and ake of te ead). concur conc low or md key ye and no tem, and ter varant, bot verbal and non-verbal; or by repetton or paraprae. confrm conf g key ye and no tem and ter varant, bot verbal and nonverbal; or by repetton or paraprae. qualfy qu qualfed tatement or by tentatve ye and no tem (were tentatvene ntonatonally gnalled) and ter varant, bot verbal ( to ome extent ye, no not really, well uppoe o (not), etc.) and non-verbal (e.g. ruggng te oulder). reject rej tatement or by ye or no tem and ter varant, bot verbal and non-verbal. May alo be realzed by lence, nterpreted a a default mecanm wereby falure to upply a re-gr, re-um,, conc, qu or approprate be an ndcaton of rejecton. ealzaton and Functon ealze... te ead of an elctng move. except at b n Clarfy and epeat excange. te ead of an elctng move at b n a Clarfy excange. te ead of an elctng move at b n a epeat excange. te ead of an elctng move at b n a e-ntaton excange or te pot-ead of any oter elctng move, or te pot-ead of a drectng move. te ead of an move at (nform excange) te ead of an move at (nform excange); or at / or (Elct excange) were te ead of te elctng move at or / realzed by eter nq or n.pr. te ead or pot-ead of an move at / or (Elct excange) were te ead of te elctng move at or / realzed by m.pr. te ead of an move at / or (Elct excange) were te ead of te elctng move at or / realzed by m.pr. te ead of an move at / or (Elct excange) were te ead of te elctng move at or / realzed by n.pr or m.pr; or te pot-ead of an anwerng, or beavng move. te ead of an anwerng move n a Structurng, Greet or Summon excange: or te ead of an move at / or (Elct excange): or te pre-ead of a beavng move n a Drect excange. Functon to elct agreement. to eek clarfcaton of a precedng utterance. to elct te repetton of a precedng utterance wc wa not clearly eard. to renforce te pont of a precedng utterance, weter t wa to elct an, a conc (etc.) or. a be. Wen t realze a move-ead, t follow a lence on te part of B to offer nformaton wc already part of te ared knowledge of te partcpant n te converaton. n oter word t a a predomnantly patc functon. to upply nformaton or to gve a decon between ye and no. to gve agreement. to gve or aert agreement. to qualfy a decon or an agreement by ndcatng tat t polarty not uncondtonal, or to detal condton and excepton. to refue to aquece to a uggeton a to te tructurng of te converaton; or to refue to gve an approprate anwer to a gr or a um, or to reject te underlyng preuppoton of an nq, n.pr or m.pr; or to ndcate unwllngne to comply wt a d. Example

24 Appendx Act Label (cont.) Label abbr. ealzed by... termnate ter low key ye and no tem, and ter varant, bot verbal and nonverbal; or by low key repetton. receve rec md key ye and no tem, and ter varant, bot verbal and nonverbal; or by md key repetton. react rea g key ye and no tem and ter varant, bot verbal and nonverbal; or by g key repetton. reformulate ref tatement wc paraprae a precedng utterance. endore end tatement or moodle tem. protet prot tatement or ye or no tem and ter varant. drectve d command. beave be acton. comment com tatement. engage mm, yea and low or md key ecoe. ealzaton and Functon ealze... te ead and/or pot-ead of an acknowledgng move at and/or F. te ead or pre-ead of an acknowledgng move at and/or F; or te pre-ead of an move at (Elctng excange); or te pre-ead of a beavng move. te ead of an acknowledgng move at and/or F. te ead of an acknowledgng move at and/or F. te ead of an acknowledgng move at and/or F. te ead of an acknowledgng move at and/or F. te ead of a drectng move. te ead of a beavng move. te pot-ead of all move except framng. Doe not realze any element of move tructure (ence t alway appear n parentee n te act column of an analy). Functon to acknowledge a precedng utterance and to termnate an excange (altoug t may be followed by furter acknowledgng move). to acknowledge a precedng utterance or (a pre-ead) to ndcate tat te approprate, be, etc. fortcomng. to ndcate potve endorement of a precedng utterance. to acknowledge a precedng utterance or offer a reved veron of t. to offer potve endorement of, ympaty wt, etc. a precedng utterance ( good dea, you poor tng, well never, very nteretng, etc.). to rae an objecton to a precedng utterance; t acknowledge te utterance wle dputng t correctne, relevance, appropratene, te partcpant rgt to ave uttered t, or anytng ele. to requet a non-verbal repone,.e. an acton. to provde a non-verbal repone to a precedng d, weter t nvolve complance, non-complance, or defance. to exemplfy, expand, explan, jutfy, provde addtonal nformaton, or evaluate one own utterance. t functon to provde mnmal feedback wle not nterruptng te flow of te oter partcpant utterance. Example

25 Appendx V: Excerpt of a one-to-one EFL converaton leon Key to ymbol paue le tan 1 econd (#) paue 1 econd or longer & nterrupted, nterruptng, or overlappng tart or fn! lence or no verbal repone Japanee word are n talc e.g. o, tabun Te followng an excerpt n md converaton about tran n Oaka Cty. Te teacer T and te tudent S. Total tme: 7 mnute 59 econd [09:41-17:40] lne of dalogue act e.. move e.. excange ex # tr # [paue] [09:41] T: Okay yea, T: te Mdouj very convenent. S: And very mple. T: Very mple. T: Uually a every econd tran goe to te end of te lne. S: mm-mm T: Umm... T: Sometme durng a peak perod S: Peak? T: Peak perod. S: Peak... S: A yea yea, know! [10:00] S: And a Na... for Nakatu and for Sn-Oaka for Sn-Kanaoka for Sn Tennoj T: a... T: Peak perod? S: Peak area. S: No? T: No, no, peak perod, S: peak per... a T: t tme. a perod of tme S: Ha, a, a m ob ref rec com ter m ob ret m com ret n.pr rej rec ref ter pot- pot- pre- pre- elctng elctng elctng F F b b / / F F nform nform (ncomplete) Clarfy nform (ncomplete) Clarfy T: So T: mornng ru our and a evenng ru our. Tey ave& S: &[unclear] troug? T: Well T: tey ave more tran& S: &yea, yea, yea ob ret rea pre- pre- elctng b b F e-ntaton (ncomplete) Clarfy T: and a o T: uually t a lke gong out, t a Tennoj, or& S: &yea, yea& T: &and ometme Abko umm but a uually t alternatng Nakamozu, Tennoj, Nakamozu, Tennoj. Durng te peak perod umm f tey ave an rregular pattern, t alway Tennoj two tran Tennoj. S: a T: a orry, [11:00] T: Nakamozu. Two tran to Nakamozu. Never two tran n a row& S: &mm& ob ob pre- b b e-ntaton (ncomplete) epeat

26 Appendx V: Excerpt of a one-to-one EFL converaton leon (cont.) lne of dalogue act e.. move e.. excange ex # tr # 36 S: &mm& 37 T: &to Tennoj& 38 S: &mm& T: &So f& S: &[unclear]& [tre to nterrupt] T: &Sorry, T: o we don t ave te problem tat you ave were two local tran. S: yea, yea T: So T: you m local tran and you tnk, a, te next one gong to go T: No, you don t ave tat problem on Mdouj. S: Wen arrve S: wen arrved at platform T: mm S: already mne wa comng T: mm S: but a forgot forget to ceck a wat knd of tran T: mm yea S: and made a mtake. T: Wat colour te local tran? S: a tran yea, yea S: tran lne colour te ame, but orange& T: &Yea T: tere a gn on te tran. T: Wat colour tat? S: A colour mm... [12:00] S: black and wte T: And te em-expre? S: em-expre and a (#) Green and wte. T: Okay, [fallng ntonaton] T: caue a & S: &t very mall. [laug] T: alway fnd t very confung wen ave to cange dfferent tran lne S: mm T: So te a Kntetu, wc wa on t mornng, blue. t te local. S: yea, yea T: But on te a (#) Kean t a black and wte. S: yea, yea T: And green te ame. Tey alo ave orange. But on te Knte on te Kean t red. [fallng ntonaton] S: But but n (#) S: n many cae a (#) about Japanee tran T: mm S: f wen wa nde te tran [13:00] T: mm-m S: We can could not could not u know a wat knd of a type wat knd of type (#) T: Or, T: don t know wat tran. S: Wat type of tran T: Or wat tran you re on. (ob) ter ob rec m ref ter ob com nq m nq ret com m ob m p ref ref pre- () pot- pre- pot- pre- pre- pre- pre- pot- pre- () elctng elctng elctng elctng b b b b b b F nform (ncomplete) (ncomplete) e-ntaton (ncomplete) e-ntaton Elct (ncomplete) Clarfy Clarfy nform (ncomplete) nform e-ntaton nform (ncomplete) Clarfy a 17 16b S: mm 86 T: Don t tey make an announcement? n.pr elctng Elct S: Sometme, ometme e ad& S: ometme [bot laug] [an n-joke] T: &ometme rec com pot- 25

27 Appendx V: Excerpt of a one-to-one EFL converaton leon (cont.) lne of dalogue act e.. move e.. excange ex # tr # T: &ometme S: not every tme& T: &um& [aborted nterjecton] b e-ntaton S: &becaue becaue too too many taton bult n Kean lne com pot T: Well... [md key] T: Well [g key] T: gue f you go by te tme T: you get to te next taton, you know, Okay t a local. S: And, yea, (#) S: o, ave (#) ave cecked a (#) n te tran [14:02] T: mm S: and a (#) wen a (#) S: a orry a S wen wen arrved at Morguc taton T: mm-m S: a (#) earced a (#) to ee outde to ee t tran [laug] my tran wat my tran? Sometme ceck ter m ob rec m pre- pre- b nform nform (ncomplete) e-ntaton T: mm T: aven t ad a uc problem. T: But a now T: before you told me T: t te lat everal year S: mm-m T: te trd cedule cange? S: trd cedule cange? T: on te Kean lne& S: &yea yea T: So, T: before t wa em-expre and local all day, [fallng ntonaton] S: mm yea T: and ten tey cut te em-expre, [fallng ntonaton] S: yea T: and now tey ve put back S: yea T: te em-expre? [fallng ntonaton] S: yea... [15:00] T: Tat frutratng! S: [laug] Yea, m ter m n.pr ret ter ret rec ret rec ret rec ter ter pre- pre- elctng elctng elctng elctng elctng b / b b b F F Elct (ncomplete) Clarfy Clarfy Clarfy Clarfy S: o (#) [fallng ntonaton] m nform S: and (#) now (#) S: actually now (#) tmetable very good S: but but& T: &For now& S: & ave to ave to be careful. [laug] T: mm T: And maybe n two year t ll cange agan. S: a o S: Yea yea yea (#) S: a o (#) Untl lat one wa angry [laug] ob qu (ter) qu ob rec rea com pre- pot- () pot- pre- pre- pot- () () nform T: How long dd tey ave te old cedule? S: Old cedule? T: Yea S: Every ten mnute. T: No, nq nq prot elctng elctng / / F Elct 33 26

28 Appendx V: Excerpt of a one-to-one EFL converaton leon (cont.) lne of dalogue act e.. move e.. excange ex # tr # T: No, T: ow long& S: Local tran comng for every& T: &every ten mnute& S: &every ten mnute T: a But, [16:00] T: mean a everal year ago tey canged te cedule S: yea T: only local& S: &ayy...& T: wen dd tey cange (#) ow long, two year, tree year? S: Two a two two year. Tabun maybe many people wa angry and u Kean [laug] S: Kean needed needed to cange. [laug] T: yea (#) T: Tey canged, wat, t weekend, or Aprl? S: a (#) Aprl t weekend S: no no no lat lat weekend (#) 16 t. T: Tat trange, not Aprl 1 t S: [laug] T: uually everytng Aprl 1 t. S: Aprl [laug] 15 t & T: &16 t S: yea S: Kean lne alway very trange. T: Well, T: t rae an nteretng queton: T: Wc tran lne not trange? [17:00] S:! T: Wc tran lne not trange? S: A (#) [uncertan] T: And before T: we talked about Hankyu taff a are very trange.& S: &[laug]& T: &Kntetu very trange know tat, tey re never on tme. S: tnk (#) S: te (#) te (#) te (#) te mot normal (#) tnk a (#) tat te mot normal a (#) Mdouj Lne. T: mm yea, prot ret () m nq com ter nq com rea ter ob ret rea com m ob be ob ob be rec rea rec () pre- pot- pot- pre- pre- pre- pre- elctng () elctng elctng elctng elctng beavng F b (/) F F F b b b F epeat (ncomplete) nform Elct (ncomplete) (ncomplete) Elct Elct nform Clarfy nform re-ntaton (ncomplete) re-ntaton T: tnk o. [17:40] -End of Analy- ter 27

29 Appendx V: Trancrpt At a café at te Toyo Hotel Oaka May 24, 2006 [paue] [09:41] T: Okay yea, te Mdouj very convenent. S: And very mple. T: Very mple. Uually a every econd tran goe to te end of te lne. S: mm-mm T: Umm... Sometme durng a peak perod S: Peak? T: Peak perod. S: Peak... A yea yea, know! And a Na... for Nakatu and for Sn-Oaka for Sn-Kanaoka for Sn Tennoj [10:00] T: a... Peak perod? S: Peak area. No? T: No, no, peak perod, S: peak per... a T: t tme. a perod of tme S: Ha, a, a T: So mornng ru our and a evenng ru our. Tey ave& S: &[unclear] troug? T: Well tey ave more tran& S: &yea, yea, yea T: and a o uually t a lke gong out, t a Tennoj, or& S: &yea, yea& T: &and ometme Abko umm but a uually t alternatng Nakamozu, Tennoj, Nakamozu, Tennoj. Durng te peak perod umm f tey ave an rregular pattern, t alway Tennoj two tran Tennoj. S: a T: a orry, Nakamozu. Two tran to Nakamozu. Never two tran n a row& [11:00] S: &mm& T: &to Tennoj& S: &mm& T: &So f...& S: &[unclear]& [tre to nterrupt] T: &Sorry, o we don t ave te problem tat you ave were two local tran. 28

30 S: yea, yea T: So you m local tran and you tnk, a, te next one gong to go No, you don t ave tat problem on Mdouj. S: Wen arrve wen arrved at platform T: mm S: already mne wa comng T: mm S: but a forgot forget to ceck a wat knd of tran T: mm yea S: and made a mtake. T: Wat colour te local tran? S: a tran yea, yea tran lne colour te ame, but orange& T: &Yea tere a gn on te tran. Wat colour tat? S: A colour mm... [12:00] S: black and wte T: And te em-expre? S: em-expre and a θ Green and wte. T: Okay, caue a & S: &t very mall. [laug] T: alway fnd t very confung wen ave to cange dfferent tran lne S: mm T: So te a Kntetu, wc wa on t mornng, blue. t te local. S: yea, yea T: But on te a θ Kean t a black and wte. S: yea, yea T: And green te ame. Tey alo ave orange. But on te Knte on te Kean t red. S: But but n θ n many cae aθ about Japanee tran T: mm S: f wen wa nde te tran [13:00] T: mm-m S: We can could not could not u know a wat knd of a type wat knd of type θ T: Or, don t know wat tran. S: Wat type of tran T: Or wat tran you re on. S: mm T: Don t tey make an announcement? S: Sometme, ometme e ad& 29

31 T/S: ometme [bot laug] [an n-joke] S: not every tme& T: &um& [aborted nterjecton] S: &becaue becaue too too many taton bult n Kean lne T: Well... Well gue f you go by te tme you get to te next taton, you know, Okay t a local. S: And, yea, θ S: o, ave θ ave cecked a θ n te tran [14:02] T: mm S: and a θ wen a θ a orry a wen wen arrved at Morguc taton T: mm-m S: a θ earced a θ to ee outde to ee t tran [laug] my tran wat my tran.?sometme ceck T: mm aven t ad a uc problem. But a now before you told me t te lat everal year S: mm-m T: te trd cedule cange? S: trd cedule cange? T: on te Kean lne& S: &yea yea T: So, before t wa em-expre and local all day, S: mm yea T: and ten tey cut te em-expre, S: yea T: and now tey ve put back S: yea T: te em-expre? S: yea... [15:00] T: Tat frutratng! S: [laug] Yea, o θ and θ now θ actually now θ tmetable very good but but& T: &For now& S: & ave to ave to be careful. [laug] T: mm And maybe n two year t ll cange agan. S: a o Yea yea yea θ a o θ Untl lat one wa angry [laug] T: How long dd tey ave te old cedule? S: Old cedule? T: Yea S: Every ten mnute. 30

32 T: No, ow long& S: &Local tran comng for every& T: &every ten mnute& S: &every ten mnute. T: a But, mean a... everal year ago tey canged te cedule [16:00] S: yea T: only local& S: &ayy...& T: &wen dd tey cange θ ow long, two year, tree year? S: Two a two two year. Tabun maybe many people wa angry and u Kean [laug] Kean needed needed to cange. [laug] T: yea θ Tey canged, wat, t weekend, or Aprl? S: a θ Aprl t weekend no no no lat lat weekend θ 16t. T: Tat trange, not Aprl 1t S: [laug] T: uually everytng Aprl 1t. S: Aprl [laug] 15 t & T: &16t S: yea Kean lne alway very trange. T: Well, t rae an nteretng queton: Wc tran lne not trange? [17:00] S: θ T: Wc tran lne not trange? S: A θ [uncertan] T: And before we talked about Hankyu taff a are very trange.& S: &[laug]& T: &Kntetu very trange know tat, tey re never on tme. S: tnk θ S: te θ te θ te θ te mot normal θ tnk a θ tat te mot normal a θ Mdouj Lne. T: mm yea, tnk o. [17:40] -End of Trancrpt- 31

33 Appendx V Due to te dffculty of catagorng te trancrbed dcoure a eter claroom dcoure or everyday dcoure requeted and receved permon to go omewat beyond wat requred by te queton. n te end decded tat dd not ave to tray too far from te agned queton. dd, owever, abandon te Snclar-Coultard model n favour of te Franc-Hunton model. Below a copy of te emal excange between myelf and Ncola Groom were e gve me permon to go beyond te requrement of te queton. All data wc may dentfy me ave been replaced wt aterk *** and rrelevant data replaced wt [ ]. Emal 1: equet From: *** <***@*mal.com> Maled-By: *mal.com To: Ncola W Groom <n.w.groom@bam.ac.uk> Date: Jun 18, :33 PM Subject: Queton About Spoken Dcoure paper Nck, am wonder wc module queton to anwer [See module queton at te end of t emal]. One baed on Franc and Hunton' 'Analyng everyday converaton', and te oter an analy of claroom Engl. Te problem tat may ave put myelf nbetween tee two. ave trancrbed a one-to-one leon wt a Oakan buneman. Wle tecncally t a "claroom" leon, t doe not follow te uual claroom dcoure pattern outlned by Snclar and Coultard. On te oter and, even toug mot leon can be called "free convertaon", t doe not ft wtn Franc and Hunton' crtera eter. t a bt of a ybrd borrowng pattern from bot. For example, we pend mnute dcung te tudent' frutraton wt te cangng tmetable of tran lne (an everyday converaton). However, neter of u n any oter context would mot lkely not pend te tme on uc a banal topc (a claroom dcuon). But bot of u are wllng to play our role a teacer & tudent becaue out purpoe to mprove Engl peakng kll. My ene to go te Snclar and Coultard route and ten add a ecton on Franc and Hunton. [ ] Ceer, *** 32

34 [ ] SD/05/03 ecord part of a converaton n Engl tat take place n one of te followng tuaton (or mlar), a outlned by Franc and Hunton (Franc, G. and Hunton, S., 'Analyng everyday converaton' n Coultard, 1992: ): caual converaton between frend and famly member cld-adult talk commercal tranacton profeonal ntervew rado pone-n Trancrbe part of your recordng, coong a part n wc tere are farly frequent alternaton of peaker. Make an analy of te trancrbed data, ung te categore propoed by Franc and Hunton (bd. p. 125 and ff.). Preent your analy a Part of your agnment. Comment on ow eay t wa to ft your data to te categore and te uefulne of t knd of analy for undertandng te knd of communcaton you ave analyed. Preent your commentary a Part of your agnment. SD/05/04 ecord one of your (or a colleague') Engl clae, and trancrbe part of your data. Make an analy of te trancrbed data, ung Snclar and Coultard' model, at te level of excange, move and act (Snclar, J. and M. Coultard, Toward an analy of dcoure: te Engl ued by teacer and pupl. Oxford: OUP 6). Comment on ow eay/dffcult t wa to ft your data to te categore and te uefulne of t knd of analy for undertandng claroom communcaton. <end of emal> ========================================================== Emal 2: eply From: Ncola W Groom <n.w.groom@bam.ac.uk> Maled-By: bam.ac.uk To: *** <***@*mal.com> Date: Jun 20, :25 AM Subject: E: Queton About Spoken Dcoure paper H *** ee wat you mean. would agree wt you tat t would probably be bet to go for te S/C one (wt H/F brougt nto te dcuon later), altoug you could n fact do eter queton, and pont out tat te data you are workng wt do not qute ft nto eter category - caual converaton or claroom dcoure n te conventonal ene. Watever you decde to do, you ould make t clafcatonal problem an explct part of te dcuon - t an nteretng pont n telf tat you are workng wt a dataet tat croe conventonallyrecogned boundare - and t n turn rae te queton of ow common uc border dcoure really ( upect muc more common tan currently recogned n dcoure reearc), and tu callenge te valdty of te categore temelve. (Tey are of corue vald n general term, but your data ow tat te boundary between tem dtnctly fuzzy). 33

E-learning Vendor Management Checklist

E-learning Vendor Management Checklist E-learning Vendor Management Checklist June 2008 Permission is granted to print freely, unmodified, this document from www.doingelearning.com or to copy it in electronic form. If linked to from the net

More information

Pass by Reference vs. Pass by Value

Pass by Reference vs. Pass by Value Pa by Reference v. Pa by Value Mot method are paed argument when they are called. An argument may be a contant or a varable. For example, n the expreon Math.qrt(33) the contant 33 paed to the qrt() method

More information

PERFORMANCE ANALYSIS OF PARALLEL ALGORITHMS

PERFORMANCE ANALYSIS OF PARALLEL ALGORITHMS Software Analye PERFORMANCE ANALYSIS OF PARALLEL ALGORIHMS Felcan ALECU PhD, Unverty Lecturer, Economc Informatc Deartment, Academy of Economc Stude, Bucharet, Romana E-mal: alecu.felcan@e.ae.ro Abtract:

More information

Service Provider SIP trunk Validation Detailed Test Plan

Service Provider SIP trunk Validation Detailed Test Plan E Document Number EDC-827327 Based on emplate EDC-206096 Rev 35 Create By Cecly Lu ervce Provder P trunk Valdaton Detaled Plan odfcatons Revson Name User d Date Comments 1 ony Banuelos tbanuelo 11/2/2009

More information

Development and use of prediction models in Building Acoustics as in EN 12354. 1 Introduction. 2 EN 12354, part 1 & 2. 2.2 Lightweight single elements

Development and use of prediction models in Building Acoustics as in EN 12354. 1 Introduction. 2 EN 12354, part 1 & 2. 2.2 Lightweight single elements evelopment and ue of predcton model n Buldng Acoutc a n EN 1354 Eddy TNO Scence and Indutry, P.O. Box 155, N-600 A elft, The Netherland, eddy.gerreten@tno.nl Improvng the acoutc clmate n buldng an mportant

More information

T1 Estimates SAT - 2006

T1 Estimates SAT - 2006 T1 Etmate SAT - 006 Tax and Lmoune Servce (TL) NAICS : 4853** by Javer Oyarzun BSMD Stattc Canada 007-1-1 1. Introducton 1.1 Ue of admntratve data Over the lat few year, Stattc Canada (STC) ha been accentuatng

More information

Section 5.4 Annuities, Present Value, and Amortization

Section 5.4 Annuities, Present Value, and Amortization Secton 5.4 Annutes, Present Value, and Amortzaton Present Value In Secton 5.2, we saw that the present value of A dollars at nterest rate per perod for n perods s the amount that must be deposted today

More information

1.1 The University may award Higher Doctorate degrees as specified from time-to-time in UPR AS11 1.

1.1 The University may award Higher Doctorate degrees as specified from time-to-time in UPR AS11 1. HIGHER DOCTORATE DEGREES SUMMARY OF PRINCIPAL CHANGES General changes None Secton 3.2 Refer to text (Amendments to verson 03.0, UPR AS02 are shown n talcs.) 1 INTRODUCTION 1.1 The Unversty may award Hgher

More information

Lecture 2: Single Layer Perceptrons Kevin Swingler

Lecture 2: Single Layer Perceptrons Kevin Swingler Lecture 2: Sngle Layer Perceptrons Kevn Sngler kms@cs.str.ac.uk Recap: McCulloch-Ptts Neuron Ths vastly smplfed model of real neurons s also knon as a Threshold Logc Unt: W 2 A Y 3 n W n. A set of synapses

More information

Updating the E5810B firmware

Updating the E5810B firmware Updatng the E5810B frmware NOTE Do not update your E5810B frmware unless you have a specfc need to do so, such as defect repar or nstrument enhancements. If the frmware update fals, the E5810B wll revert

More information

Nordea G10 Alpha Carry Index

Nordea G10 Alpha Carry Index Nordea G10 Alpha Carry Index Index Rules v1.1 Verson as of 10/10/2013 1 (6) Page 1 Index Descrpton The G10 Alpha Carry Index, the Index, follows the development of a rule based strategy whch nvests and

More information

The Development of Web Log Mining Based on Improve-K-Means Clustering Analysis

The Development of Web Log Mining Based on Improve-K-Means Clustering Analysis The Development of Web Log Mnng Based on Improve-K-Means Clusterng Analyss TngZhong Wang * College of Informaton Technology, Luoyang Normal Unversty, Luoyang, 471022, Chna wangtngzhong2@sna.cn Abstract.

More information

To manage leave, meeting institutional requirements and treating individual staff members fairly and consistently.

To manage leave, meeting institutional requirements and treating individual staff members fairly and consistently. Corporate Polces & Procedures Human Resources - Document CPP216 Leave Management Frst Produced: Current Verson: Past Revsons: Revew Cycle: Apples From: 09/09/09 26/10/12 09/09/09 3 years Immedately Authorsaton:

More information

Robust biometric-based user authentication scheme for wireless sensor networks

Robust biometric-based user authentication scheme for wireless sensor networks Robut bometrc-baed uer autentcaton ceme for wrele enor network Debao He* cool of Matematc and tattc Wuan nverty Wuan Cna Emal: edebao@16.com Abtract: Wrele enor network (WN) are appled wdely a varety of

More information

An Alternative Way to Measure Private Equity Performance

An Alternative Way to Measure Private Equity Performance An Alternatve Way to Measure Prvate Equty Performance Peter Todd Parlux Investment Technology LLC Summary Internal Rate of Return (IRR) s probably the most common way to measure the performance of prvate

More information

VRT012 User s guide V0.1. Address: Žirmūnų g. 27, Vilnius LT-09105, Phone: (370-5) 2127472, Fax: (370-5) 276 1380, Email: info@teltonika.

VRT012 User s guide V0.1. Address: Žirmūnų g. 27, Vilnius LT-09105, Phone: (370-5) 2127472, Fax: (370-5) 276 1380, Email: info@teltonika. VRT012 User s gude V0.1 Thank you for purchasng our product. We hope ths user-frendly devce wll be helpful n realsng your deas and brngng comfort to your lfe. Please take few mnutes to read ths manual

More information

THE ANALYSIS AND OPTIMIZATION OF SURVIVABILITY OF MPLS NETWORKS. Mohammadreza Mossavari, Yurii Zaychenko

THE ANALYSIS AND OPTIMIZATION OF SURVIVABILITY OF MPLS NETWORKS. Mohammadreza Mossavari, Yurii Zaychenko Internatonal Journal "Informaton Theore & Applcaton" Vol5 / 28 253 TE ANALYSIS AND OTIMIATION OF SURVIVABILITY OF MLS NETWORS Mohammadreza Moavar, Yur aychenko Abtract: The problem of MLS network urvvablty

More information

IT09 - Identity Management Policy

IT09 - Identity Management Policy IT09 - Identty Management Polcy Introducton 1 The Unersty needs to manage dentty accounts for all users of the Unersty s electronc systems and ensure that users hae an approprate leel of access to these

More information

Basic Principle of Buck-Boost

Basic Principle of Buck-Boost Bac Prncple of Buck-Boot he buck-boot a popular non-olated nvertng power tage topology, ometme called a tep-up/down power tage. Power upply degner chooe the buck-boot power tage becaue the requred output

More information

Extending Probabilistic Dynamic Epistemic Logic

Extending Probabilistic Dynamic Epistemic Logic Extendng Probablstc Dynamc Epstemc Logc Joshua Sack May 29, 2008 Probablty Space Defnton A probablty space s a tuple (S, A, µ), where 1 S s a set called the sample space. 2 A P(S) s a σ-algebra: a set

More information

Multifunction Phased Array Radar Resource Management: Real-Time Scheduling Algorithm

Multifunction Phased Array Radar Resource Management: Real-Time Scheduling Algorithm Journal of Computatonal Informaton Sytem 7:2 (211) 385-393 Avalable at http://www.jofc.com Multfuncton Phaed Array Radar Reource Management: Real-me Schedulng Algorm Janbn LU 1,, Hu XIAO 2, Zemn XI 1,

More information

An Interest-Oriented Network Evolution Mechanism for Online Communities

An Interest-Oriented Network Evolution Mechanism for Online Communities An Interest-Orented Network Evoluton Mechansm for Onlne Communtes Cahong Sun and Xaopng Yang School of Informaton, Renmn Unversty of Chna, Bejng 100872, P.R. Chna {chsun,yang}@ruc.edu.cn Abstract. Onlne

More information

Modeling ISP Tier Design

Modeling ISP Tier Design Modelng ISP Ter Degn We Da School of Informaton and Computer Scence Unverty of Calforna, Irvne Irvne, CA, US daw1@uc.edu Scott Jordan School of Informaton and Computer Scence Unverty of Calforna, Irvne

More information

The Cox-Ross-Rubinstein Option Pricing Model

The Cox-Ross-Rubinstein Option Pricing Model Fnance 400 A. Penat - G. Pennacc Te Cox-Ross-Rubnsten Opton Prcng Model Te prevous notes sowed tat te absence o arbtrage restrcts te prce o an opton n terms o ts underlyng asset. However, te no-arbtrage

More information

Module 2 LOSSLESS IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur

Module 2 LOSSLESS IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur Module LOSSLESS IMAGE COMPRESSION SYSTEMS Lesson 3 Lossless Compresson: Huffman Codng Instructonal Objectves At the end of ths lesson, the students should be able to:. Defne and measure source entropy..

More information

What is Candidate Sampling

What is Candidate Sampling What s Canddate Samplng Say we have a multclass or mult label problem where each tranng example ( x, T ) conssts of a context x a small (mult)set of target classes T out of a large unverse L of possble

More information

Small pots lump sum payment instruction

Small pots lump sum payment instruction For customers Small pots lump sum payment nstructon Please read these notes before completng ths nstructon About ths nstructon Use ths nstructon f you re an ndvdual wth Aegon Retrement Choces Self Invested

More information

CISCO SPA500G SERIES REFERENCE GUIDE

CISCO SPA500G SERIES REFERENCE GUIDE CISCO SPA500G SERIES REFERENCE GUIDE Part of the Csco Small Busness Pro Seres, the SIP based Csco SPA504G 4-Lne IP phone wth 2-port swtch has been tested to ensure comprehensve nteroperablty wth equpment

More information

Vembu StoreGrid Windows Client Installation Guide

Vembu StoreGrid Windows Client Installation Guide Ser v cepr ov dered t on Cl enti nst al l at ongu de W ndows Vembu StoreGrd Wndows Clent Installaton Gude Download the Wndows nstaller, VembuStoreGrd_4_2_0_SP_Clent_Only.exe To nstall StoreGrd clent on

More information

Lecture 3: Force of Interest, Real Interest Rate, Annuity

Lecture 3: Force of Interest, Real Interest Rate, Annuity Lecture 3: Force of Interest, Real Interest Rate, Annuty Goals: Study contnuous compoundng and force of nterest Dscuss real nterest rate Learn annuty-mmedate, and ts present value Study annuty-due, and

More information

Financial Mathemetics

Financial Mathemetics Fnancal Mathemetcs 15 Mathematcs Grade 12 Teacher Gude Fnancal Maths Seres Overvew In ths seres we am to show how Mathematcs can be used to support personal fnancal decsons. In ths seres we jon Tebogo,

More information

Positive Integral Operators With Analytic Kernels

Positive Integral Operators With Analytic Kernels Çnky Ünverte Fen-Edeyt Fkülte, Journl of Art nd Scence Sy : 6 / Arl k 006 Potve ntegrl Opertor Wth Anlytc Kernel Cn Murt D KMEN Atrct n th pper we contruct exmple of potve defnte ntegrl kernel whch re

More information

How To Model A Multi-Home

How To Model A Multi-Home The Impact of the Internet on Advertng Market for New Meda by Suan Athey, Emlo Calvano and Johua S. Gan * Frt raft: October, 009 Th Veron: Aprl 03 In th paper, we explore the hypothe that an mportant force

More information

Hollinger Canadian Publishing Holdings Co. ( HCPH ) proceeding under the Companies Creditors Arrangement Act ( CCAA )

Hollinger Canadian Publishing Holdings Co. ( HCPH ) proceeding under the Companies Creditors Arrangement Act ( CCAA ) February 17, 2011 Andrew J. Hatnay ahatnay@kmlaw.ca Dear Sr/Madam: Re: Re: Hollnger Canadan Publshng Holdngs Co. ( HCPH ) proceedng under the Companes Credtors Arrangement Act ( CCAA ) Update on CCAA Proceedngs

More information

A powerful tool designed to enhance innovation and business performance

A powerful tool designed to enhance innovation and business performance A powerful tool desgned to enhance nnovaton and busness performance The LEGO Foundaton has taken over the responsblty for the LEGO SERIOUS PLAY method. Ths change wll help create the platform for the contnued

More information

Evidence for Adverse Selection in the Automobile Insurance Market

Evidence for Adverse Selection in the Automobile Insurance Market Evdence for Adverse Selecton n te Automoble Insurance Market Racel J. Huang * Assstant Professor, Fnance Department Mng Cuan Unversty, Tape, Tawan Larry Y. Tzeng Professor, Department of Fnance Natonal

More information

Applying the Value/Petri Process to ERP Software Development in China

Applying the Value/Petri Process to ERP Software Development in China Applyng the Value/Petr Proce to ERP Software Development n Chna LGuo Huang Barry Boehm Computer Scence Department Unverty of Southern Calforna Lo Angele, CA 90089-0781, USA 001 213-740-6470 {lguohua, boehm}@

More information

HALL EFFECT SENSORS AND COMMUTATION

HALL EFFECT SENSORS AND COMMUTATION OEM770 5 Hall Effect ensors H P T E R 5 Hall Effect ensors The OEM770 works wth three-phase brushless motors equpped wth Hall effect sensors or equvalent feedback sgnals. In ths chapter we wll explan how

More information

The issue of whether the Internet will permanently destroy the news media is currently a

The issue of whether the Internet will permanently destroy the news media is currently a Wll the Internet etroy the New Meda? or Can Onlne Advertng Market Save the Meda? by Suan Athey, Emlo Calvano and Johua S. Gan * Frt raft: October, 009 Th Veron: November, 00 PRELIMINARY PLEASE O NOT QUOTE

More information

New method for grain size characterization of a multi-crystalline silicon ingot

New method for grain size characterization of a multi-crystalline silicon ingot New method for gran ze characterzaton of a mult-crytallne lcon ngot Maxme Forter, Erwann Fourmond, Jean-Mare Lebrun, Roland Enhau, Jed Kraem, Mutapha Lemt To cte th veron: Maxme Forter, Erwann Fourmond,

More information

Tuition Fee Loan application notes

Tuition Fee Loan application notes Tuton Fee Loan applcaton notes for new part-tme EU students 2012/13 About these notes These notes should be read along wth your Tuton Fee Loan applcaton form. The notes are splt nto three parts: Part 1

More information

ITS-90 FORMULATIONS FOR VAPOR PRESSURE, FROSTPOINT TEMPERATURE, DEWPOINT TEMPERATURE, AND ENHANCEMENT FACTORS IN THE RANGE 100 TO +100 C.

ITS-90 FORMULATIONS FOR VAPOR PRESSURE, FROSTPOINT TEMPERATURE, DEWPOINT TEMPERATURE, AND ENHANCEMENT FACTORS IN THE RANGE 100 TO +100 C. ITS-90 FORMULATIONS FOR VAPOR PRESSURE, FROSTPOINT TEMPERATURE, DEWPOINT TEMPERATURE, AND ENHANCEMENT FACTORS IN THE RANGE 100 TO +100 C Bob Hardy Thunder Scentfc Corporaton, Albuquerque, NM, USA Abtract:

More information

Overview of monitoring and evaluation

Overview of monitoring and evaluation 540 Toolkt to Combat Traffckng n Persons Tool 10.1 Overvew of montorng and evaluaton Overvew Ths tool brefly descrbes both montorng and evaluaton, and the dstncton between the two. What s montorng? Montorng

More information

Payback Period Estimation of Ground-Source and Air-Source Multi Heat Pumps in Korea Based on Yearly Running Cost Simulation

Payback Period Estimation of Ground-Source and Air-Source Multi Heat Pumps in Korea Based on Yearly Running Cost Simulation Purdue nverty Purdue e-pub Internatonal Refrgeraton and Ar ondtonng onference Scool of Mecancal Engneerng 00 Payback Perod Etmaton of Ground-Source and Ar-Source Mult Heat Pump n Korea Baed on Yearly Runnng

More information

How To Understand Propect Theory And Mean Variance Analysis

How To Understand Propect Theory And Mean Variance Analysis Invetment Management and Fnancal Innovaton, Volume 6, Iue 1, 2009 Enrco De Gorg (Swtzerland ), Thorten Hen (Swtzerland) Propect theory and mean-varance analy: doe t make a dfference n wealth management?

More information

Certificate No. 68613082 ONTARIO COURT (PROVINCIAL DIVISION) - versus - PAULO RAPOSO TRANSCRIPT OF PROCEEDINGS

Certificate No. 68613082 ONTARIO COURT (PROVINCIAL DIVISION) - versus - PAULO RAPOSO TRANSCRIPT OF PROCEEDINGS Certfcate No. 686182 ONTARIO COURT (PROVINCIAL DIVISION) HER MAJESTY THE QUEEN - versus - PAULO RAPOSO TRANSCRIPT OF PROCEEDINGS Heard before The Honourable Mr. Justce D. Cooper at Hamlton, Ontaro on Aprl

More information

CHOLESTEROL REFERENCE METHOD LABORATORY NETWORK. Sample Stability Protocol

CHOLESTEROL REFERENCE METHOD LABORATORY NETWORK. Sample Stability Protocol CHOLESTEROL REFERENCE METHOD LABORATORY NETWORK Sample Stablty Protocol Background The Cholesterol Reference Method Laboratory Network (CRMLN) developed certfcaton protocols for total cholesterol, HDL

More information

T3 Comfort connected to IP Office

T3 Comfort connected to IP Office elephony IP T Contact Centers Moblty Servces T3 Comfort connected to IP Offce Benutzerhandbuch User s gude Manual de usuaro Manuel utlsateur Manuale d uso Gebrukersdocumentate Contents Content Famlarse

More information

ARTICLE IN PRESS. JID:COMAID AID:1153 /FLA [m3g; v 1.79; Prn:21/02/2009; 14:10] P.1 (1-13) Computer Aided Geometric Design ( )

ARTICLE IN PRESS. JID:COMAID AID:1153 /FLA [m3g; v 1.79; Prn:21/02/2009; 14:10] P.1 (1-13) Computer Aided Geometric Design ( ) COMAID:5 JID:COMAID AID:5 /FLA [mg; v 79; Prn:/0/009; 4:0] P -) Computer Aded Geometrc Degn ) Content lt avalable at ScenceDrect Computer Aded Geometrc Degn wwwelevercom/locate/cagd Fat approach for computng

More information

1. Measuring association using correlation and regression

1. Measuring association using correlation and regression How to measure assocaton I: Correlaton. 1. Measurng assocaton usng correlaton and regresson We often would lke to know how one varable, such as a mother's weght, s related to another varable, such as a

More information

How To Ensure That An Eac Edge Program Is Successful

How To Ensure That An Eac Edge Program Is Successful Introduction Te Economic Diversification and Growt Enterprises Act became effective on 1 January 1995. Te creation of tis Act was to encourage new businesses to start or expand in Newfoundland and Labrador.

More information

Linear Circuits Analysis. Superposition, Thevenin /Norton Equivalent circuits

Linear Circuits Analysis. Superposition, Thevenin /Norton Equivalent circuits Lnear Crcuts Analyss. Superposton, Theenn /Norton Equalent crcuts So far we hae explored tmendependent (resste) elements that are also lnear. A tmendependent elements s one for whch we can plot an / cure.

More information

Project Management Basics

Project Management Basics Project Management Baic A Guide to undertanding the baic component of effective project management and the key to ucce 1 Content 1.0 Who hould read thi Guide... 3 1.1 Overview... 3 1.2 Project Management

More information

Calculating the high frequency transmission line parameters of power cables

Calculating the high frequency transmission line parameters of power cables < ' Calculatng the hgh frequency transmsson lne parameters of power cables Authors: Dr. John Dcknson, Laboratory Servces Manager, N 0 RW E B Communcatons Mr. Peter J. Ncholson, Project Assgnment Manager,

More information

Feature selection for intrusion detection. Slobodan Petrović NISlab, Gjøvik University College

Feature selection for intrusion detection. Slobodan Petrović NISlab, Gjøvik University College Feature selecton for ntruson detecton Slobodan Petrovć NISlab, Gjøvk Unversty College Contents The feature selecton problem Intruson detecton Traffc features relevant for IDS The CFS measure The mrmr measure

More information

Joe Pimbley, unpublished, 2005. Yield Curve Calculations

Joe Pimbley, unpublished, 2005. Yield Curve Calculations Joe Pmbley, unpublshed, 005. Yeld Curve Calculatons Background: Everythng s dscount factors Yeld curve calculatons nclude valuaton of forward rate agreements (FRAs), swaps, nterest rate optons, and forward

More information

AT&T Small Business System Speakerphone with Digital Answering System and Caller ID/Call Waiting 984

AT&T Small Business System Speakerphone with Digital Answering System and Caller ID/Call Waiting 984 984CIB_(Rev9)ml_24.05.06 5/24/06 8:07 PM Page 1 USER S MANUAL Part 2 AT&T Small Busness System Speakerphone wth Dgtal Answerng System and Caller ID/Call Watng 984 For Customer Servce Or Product Informaton,

More information

Traffic-light a stress test for life insurance provisions

Traffic-light a stress test for life insurance provisions MEMORANDUM Date 006-09-7 Authors Bengt von Bahr, Göran Ronge Traffc-lght a stress test for lfe nsurance provsons Fnansnspetonen P.O. Box 6750 SE-113 85 Stocholm [Sveavägen 167] Tel +46 8 787 80 00 Fax

More information

On-Line Fault Detection in Wind Turbine Transmission System using Adaptive Filter and Robust Statistical Features

On-Line Fault Detection in Wind Turbine Transmission System using Adaptive Filter and Robust Statistical Features On-Lne Fault Detecton n Wnd Turbne Transmsson System usng Adaptve Flter and Robust Statstcal Features Ruoyu L Remote Dagnostcs Center SKF USA Inc. 3443 N. Sam Houston Pkwy., Houston TX 77086 Emal: ruoyu.l@skf.com

More information

Texas Instruments 30X IIS Calculator

Texas Instruments 30X IIS Calculator Texas Instruments 30X IIS Calculator Keystrokes for the TI-30X IIS are shown for a few topcs n whch keystrokes are unque. Start by readng the Quk Start secton. Then, before begnnng a specfc unt of the

More information

Simple Interest Loans (Section 5.1) :

Simple Interest Loans (Section 5.1) : Chapter 5 Fnance The frst part of ths revew wll explan the dfferent nterest and nvestment equatons you learned n secton 5.1 through 5.4 of your textbook and go through several examples. The second part

More information

The Impact of the Internet on Advertising Markets for News Media

The Impact of the Internet on Advertising Markets for News Media The Impact of the Internet on Advertng Market for New Meda by Suan Athey, Emlo Calvano and Johua S. Gan * Frt Draft: October, 009 Th Veron: October 0 In th paper, we explore the hypothe that an mportant

More information

DEFINING %COMPLETE IN MICROSOFT PROJECT

DEFINING %COMPLETE IN MICROSOFT PROJECT CelersSystems DEFINING %COMPLETE IN MICROSOFT PROJECT PREPARED BY James E Aksel, PMP, PMI-SP, MVP For Addtonal Informaton about Earned Value Management Systems and reportng, please contact: CelersSystems,

More information

CHAPTER-II WATER-FLOODING. Calculating Oil Recovery Resulting from Displ. by an Immiscible Fluid:

CHAPTER-II WATER-FLOODING. Calculating Oil Recovery Resulting from Displ. by an Immiscible Fluid: CHAPTER-II WATER-FLOODING Interfacal Tenson: Energy requred ncreasng te area of te nterface by one unt. Te metods of measurng IFT s nclude a rng tensometer, pendant drop and spnnng drop tecnques. IFT s

More information

GENESYS BUSINESS MANAGER

GENESYS BUSINESS MANAGER GENESYS BUSINESS MANAGER e-manager Onlne Conference User Account Admnstraton User Gude Ths User Gude contans the followng sectons: Mnmum Requrements...3 Gettng Started...4 Sgnng On to Genesys Busness Manager...7

More information

IDENTIFICATION AND CORRECTION OF A COMMON ERROR IN GENERAL ANNUITY CALCULATIONS

IDENTIFICATION AND CORRECTION OF A COMMON ERROR IN GENERAL ANNUITY CALCULATIONS IDENTIFICATION AND CORRECTION OF A COMMON ERROR IN GENERAL ANNUITY CALCULATIONS Chrs Deeley* Last revsed: September 22, 200 * Chrs Deeley s a Senor Lecturer n the School of Accountng, Charles Sturt Unversty,

More information

Estimating the Development Effort of Web Projects in Chile

Estimating the Development Effort of Web Projects in Chile Estmatng the Development Effort of Web Projects n Chle Sergo F. Ochoa Computer Scences Department Unversty of Chle (56 2) 678-4364 sochoa@dcc.uchle.cl M. Cecla Bastarrca Computer Scences Department Unversty

More information

Hospital care organisation in Italy: a theoretical assessment of the reform

Hospital care organisation in Italy: a theoretical assessment of the reform Dartmento d Scenze Economche Unvertà d Breca Va S. Fautno 7/b 5 BESCIA Tel. 3 98885 Fax. 3 988837 e-mal: levagg@eco.unb.t otal care organaton n Italy: a theoretcal aement of the reform oella evagg Abtract.

More information

The Design of Reliable Trust Management Systems for Electronic Trading Communities

The Design of Reliable Trust Management Systems for Electronic Trading Communities The Degn of Relale Trut Management Sytem for Electronc Tradng Communte Chryantho Dellaroca Sloan School of Management Maachuett Inttute of Technology Room E53-315 Camrdge, MA 02139 dell@mt.edu Atract:

More information

benefit is 2, paid if the policyholder dies within the year, and probability of death within the year is ).

benefit is 2, paid if the policyholder dies within the year, and probability of death within the year is ). REVIEW OF RISK MANAGEMENT CONCEPTS LOSS DISTRIBUTIONS AND INSURANCE Loss and nsurance: When someone s subject to the rsk of ncurrng a fnancal loss, the loss s generally modeled usng a random varable or

More information

Coordinate System for 3-D Model Used in Robotic End-Effector

Coordinate System for 3-D Model Used in Robotic End-Effector AU JT 8(: 8 (Apr Codnate Sytem f D Model Ued n Robot EndEffer ulfqar Al Soomro Shool of Advaned Stude, Aan Inttute of Tehnology Pathum Than, Thaland Abtrat Th paper reve the onept of odnate ytem on new

More information

VOLUME 7 SECTION 3A REGISTRATION OF COMPANIES CUSTOMER GUIDELINES BASED ON COMPANIES ACT 2004

VOLUME 7 SECTION 3A REGISTRATION OF COMPANIES CUSTOMER GUIDELINES BASED ON COMPANIES ACT 2004 regstraton of companes.qxp 02/05/2007 09:55 AM Page 1 VOLUME 7 SECTION 3A REGISTRATION OF COMPANIES CUSTOMER GUIDELINES BASED ON COMPANIES ACT 2004 The Responsblty of The Companes Offce of Jamaca (formerly

More information

BEST-IN-CLASS VENDOR COMPLIANCE BURLINGTON COAT FACTORY

BEST-IN-CLASS VENDOR COMPLIANCE BURLINGTON COAT FACTORY BEST-IN-CLASS VENDOR COMPLIANCE BURLINGTON COAT FACTORY A best n class Vendor Complance program enabled Burlngton Coat Factory to gan control of ther supply chans by provdng accountablty for vendors and

More information

RELIABILITY, RISK AND AVAILABILITY ANLYSIS OF A CONTAINER GANTRY CRANE ABSTRACT

RELIABILITY, RISK AND AVAILABILITY ANLYSIS OF A CONTAINER GANTRY CRANE ABSTRACT Kolowrock Krzysztof Joanna oszynska MODELLING ENVIRONMENT AND INFRATRUCTURE INFLUENCE ON RELIABILITY AND OPERATION RT&A # () (Vol.) March RELIABILITY RIK AND AVAILABILITY ANLYI OF A CONTAINER GANTRY CRANE

More information

Control and Coordination of Interactive Videoconferencing over Hybrid Networks

Control and Coordination of Interactive Videoconferencing over Hybrid Networks 1 of 5 ontrol and oordnaton of Interactve Vdeoconferencng over Hybrd Network Tng-hao Hou, horng-horng Yang., Yun-Sun hu, and Km-Joan hen epartment of Electrcal Engneerng Natonal hung heng Unverty 160,

More information

Section 5.3 Annuities, Future Value, and Sinking Funds

Section 5.3 Annuities, Future Value, and Sinking Funds Secton 5.3 Annutes, Future Value, and Snkng Funds Ordnary Annutes A sequence of equal payments made at equal perods of tme s called an annuty. The tme between payments s the payment perod, and the tme

More information

Section C2: BJT Structure and Operational Modes

Section C2: BJT Structure and Operational Modes Secton 2: JT Structure and Operatonal Modes Recall that the semconductor dode s smply a pn juncton. Dependng on how the juncton s based, current may easly flow between the dode termnals (forward bas, v

More information

Multiple-Period Attribution: Residuals and Compounding

Multiple-Period Attribution: Residuals and Compounding Multple-Perod Attrbuton: Resduals and Compoundng Our revewer gave these authors full marks for dealng wth an ssue that performance measurers and vendors often regard as propretary nformaton. In 1994, Dens

More information

A Probabilistic Theory of Coherence

A Probabilistic Theory of Coherence A Probablstc Theory of Coherence BRANDEN FITELSON. The Coherence Measure C Let E be a set of n propostons E,..., E n. We seek a probablstc measure C(E) of the degree of coherence of E. Intutvely, we want

More information

The Current Employment Statistics (CES) survey,

The Current Employment Statistics (CES) survey, Busness Brths and Deaths Impact of busness brths and deaths n the payroll survey The CES probablty-based sample redesgn accounts for most busness brth employment through the mputaton of busness deaths,

More information

Risk-based Fatigue Estimate of Deep Water Risers -- Course Project for EM388F: Fracture Mechanics, Spring 2008

Risk-based Fatigue Estimate of Deep Water Risers -- Course Project for EM388F: Fracture Mechanics, Spring 2008 Rsk-based Fatgue Estmate of Deep Water Rsers -- Course Project for EM388F: Fracture Mechancs, Sprng 2008 Chen Sh Department of Cvl, Archtectural, and Envronmental Engneerng The Unversty of Texas at Austn

More information

Abstract. 2.2. Adjusted PPM.

Abstract. 2.2. Adjusted PPM. Effectvene of Avance an Authentcate Packet Markng Scheme for Traceback of Denal of Servce Attack Blal Rzv an Emmanuel Fernánez-Gaucheran Department of Electrcal & Computer Engneerng &Computer Scence Unverty

More information

Support Vector Machines

Support Vector Machines Support Vector Machnes Max Wellng Department of Computer Scence Unversty of Toronto 10 Kng s College Road Toronto, M5S 3G5 Canada wellng@cs.toronto.edu Abstract Ths s a note to explan support vector machnes.

More information

Time Value of Money. Types of Interest. Compounding and Discounting Single Sums. Page 1. Ch. 6 - The Time Value of Money. The Time Value of Money

Time Value of Money. Types of Interest. Compounding and Discounting Single Sums. Page 1. Ch. 6 - The Time Value of Money. The Time Value of Money Ch. 6 - The Tme Value of Money Tme Value of Money The Interest Rate Smple Interest Compound Interest Amortzng a Loan FIN21- Ahmed Y, Dasht TIME VALUE OF MONEY OR DISCOUNTED CASH FLOW ANALYSIS Very Important

More information

7.5. Present Value of an Annuity. Investigate

7.5. Present Value of an Annuity. Investigate 7.5 Present Value of an Annuty Owen and Anna are approachng retrement and are puttng ther fnances n order. They have worked hard and nvested ther earnngs so that they now have a large amount of money on

More information

21 Vectors: The Cross Product & Torque

21 Vectors: The Cross Product & Torque 21 Vectors: The Cross Product & Torque Do not use our left hand when applng ether the rght-hand rule for the cross product of two vectors dscussed n ths chapter or the rght-hand rule for somethng curl

More information

A Novel Architecture Design of Large-Scale Distributed Object Storage System

A Novel Architecture Design of Large-Scale Distributed Object Storage System Internatonal Journal of Grd Dtrbuton Computng Vol.8, No.1 (2015), pp.25-32 http://dx.do.org/10.14257/gdc.2015.8.1.03 A Novel Archtecture Degn of Large-Scale Dtrbuted Obect Storage Sytem Shan Yng 1 and

More information

Trade Adjustment and Productivity in Large Crises. Online Appendix May 2013. Appendix A: Derivation of Equations for Productivity

Trade Adjustment and Productivity in Large Crises. Online Appendix May 2013. Appendix A: Derivation of Equations for Productivity Trade Adjustment Productvty n Large Crses Gta Gopnath Department of Economcs Harvard Unversty NBER Brent Neman Booth School of Busness Unversty of Chcago NBER Onlne Appendx May 2013 Appendx A: Dervaton

More information

Hosted Voice Self Service Installation Guide

Hosted Voice Self Service Installation Guide Hosted Voce Self Servce Installaton Gude Contact us at 1-877-355-1501 learnmore@elnk.com www.earthlnk.com 2015 EarthLnk. Trademarks are property of ther respectve owners. All rghts reserved. 1071-07629

More information

Tangent Lines and Rates of Change

Tangent Lines and Rates of Change Tangent Lines and Rates of Cange 9-2-2005 Given a function y = f(x), ow do you find te slope of te tangent line to te grap at te point P(a, f(a))? (I m tinking of te tangent line as a line tat just skims

More information

Unit 11 Using Linear Regression to Describe Relationships

Unit 11 Using Linear Regression to Describe Relationships Unit 11 Uing Linear Regreion to Decribe Relationhip Objective: To obtain and interpret the lope and intercept of the leat quare line for predicting a quantitative repone variable from a quantitative explanatory

More information

MASSACHUSETTS DEPARTMENT OF CORRECTION EMPLOYEE PERFORMANCE EVALUATION 103 DOC 222 TABLE OF CONTENTS 222.01 DEFINITIONS...3 222.02 GENERAL POLICY...

MASSACHUSETTS DEPARTMENT OF CORRECTION EMPLOYEE PERFORMANCE EVALUATION 103 DOC 222 TABLE OF CONTENTS 222.01 DEFINITIONS...3 222.02 GENERAL POLICY... MASSACHUSETTS DEPARTMENT OF CORRECTION EMPLOYEE PERFORMANCE EVALUATION 103 DOC 222 TABLE OF CONTENTS 222.01 DEFINITIONS...3 222.02 GENERAL POLICY...4 222.03 FREQUENCY...4 222.04 RECORDS MAINTENANCE...5

More information

Time Value of Money Module

Time Value of Money Module Tme Value of Money Module O BJECTIVES After readng ths Module, you wll be able to: Understand smple nterest and compound nterest. 2 Compute and use the future value of a sngle sum. 3 Compute and use the

More information

Recurrence. 1 Definitions and main statements

Recurrence. 1 Definitions and main statements Recurrence 1 Defntons and man statements Let X n, n = 0, 1, 2,... be a MC wth the state space S = (1, 2,...), transton probabltes p j = P {X n+1 = j X n = }, and the transton matrx P = (p j ),j S def.

More information

We assume your students are learning about self-regulation (how to change how alert they feel) through the Alert Program with its three stages:

We assume your students are learning about self-regulation (how to change how alert they feel) through the Alert Program with its three stages: Welcome to ALERT BINGO, a fun-flled and educatonal way to learn the fve ways to change engnes levels (Put somethng n your Mouth, Move, Touch, Look, and Lsten) as descrbed n the How Does Your Engne Run?

More information

LIFETIME INCOME OPTIONS

LIFETIME INCOME OPTIONS LIFETIME INCOME OPTIONS May 2011 by: Marca S. Wagner, Esq. The Wagner Law Group A Professonal Corporaton 99 Summer Street, 13 th Floor Boston, MA 02110 Tel: (617) 357-5200 Fax: (617) 357-5250 www.ersa-lawyers.com

More information

RESEARCH ON DUAL-SHAKER SINE VIBRATION CONTROL. Yaoqi FENG 1, Hanping QIU 1. China Academy of Space Technology (CAST) yaoqi.feng@yahoo.

RESEARCH ON DUAL-SHAKER SINE VIBRATION CONTROL. Yaoqi FENG 1, Hanping QIU 1. China Academy of Space Technology (CAST) yaoqi.feng@yahoo. ICSV4 Carns Australa 9- July, 007 RESEARCH ON DUAL-SHAKER SINE VIBRATION CONTROL Yaoq FENG, Hanpng QIU Dynamc Test Laboratory, BISEE Chna Academy of Space Technology (CAST) yaoq.feng@yahoo.com Abstract

More information

The OC Curve of Attribute Acceptance Plans

The OC Curve of Attribute Acceptance Plans The OC Curve of Attrbute Acceptance Plans The Operatng Characterstc (OC) curve descrbes the probablty of acceptng a lot as a functon of the lot s qualty. Fgure 1 shows a typcal OC Curve. 10 8 6 4 1 3 4

More information

An Evaluation of the Extended Logistic, Simple Logistic, and Gompertz Models for Forecasting Short Lifecycle Products and Services

An Evaluation of the Extended Logistic, Simple Logistic, and Gompertz Models for Forecasting Short Lifecycle Products and Services An Evaluaton of the Extended Logstc, Smple Logstc, and Gompertz Models for Forecastng Short Lfecycle Products and Servces Charles V. Trappey a,1, Hsn-yng Wu b a Professor (Management Scence), Natonal Chao

More information

CASE STUDY BRIDGE. www.future-processing.com

CASE STUDY BRIDGE. www.future-processing.com CASE STUDY BRIDGE TABLE OF CONTENTS #1 ABOUT THE CLIENT 3 #2 ABOUT THE PROJECT 4 #3 OUR ROLE 5 #4 RESULT OF OUR COLLABORATION 6-7 #5 THE BUSINESS PROBLEM THAT WE SOLVED 8 #6 CHALLENGES 9 #7 VISUAL IDENTIFICATION

More information